Run
40069

Run 40069

Task 3846 (Supervised Classification) cmc Uploaded 28-10-2014 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.MultiBoostAB_ADTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.ADTree(2)_B10
weka.ADTree(2)_E-3
weka.ADTree(2)_S1
weka.MultiBoostAB_ADTree(2)_C3
weka.MultiBoostAB_ADTree(2)_P100
weka.MultiBoostAB_ADTree(2)_S1
weka.MultiBoostAB_ADTree(2)_I80
weka.MultiBoostAB_ADTree(2)_Wweka.classifiers.trees.ADTree

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

21 Evaluation measures

Area under ROC curve
0.756
Per class
Cross-validation details (10-fold Crossvalidation)
Build CPU time
1.6597
Cross-validation details (10-fold Crossvalidation)
Build memory
1010005223.0767
Cross-validation details (10-fold Crossvalidation)
F measure
0.7071
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3988
Cross-validation details (10-fold Crossvalidation)
KB relative information score
575.5022
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2969
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4894
Cross-validation details (10-fold Crossvalidation)
Number of instances
1473
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7155
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7149
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9846
Cross-validation details (10-fold Crossvalidation)
Recall
0.7149
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6068
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4946
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4977
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0062
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
941.4198